Earticle

초록

영어

3D face reconstruction and 3D face recognition belonged to different fields previously. In order to solve these two issues in a unified way, this paper designed a kind of regionalized implicit function feature (RIFF) algorithm frame. Firstly according to the biology characteristic, the face was segmented to five regions with different resolutions; secondly the control matrix which expressed the human face was solved for 3d face reconstruction; then dimensionality reduction was did for this control matrix; finally the low dimensional character description was computed completely for 3d face classification. The specific experiments for the RIFF method are performed and the results show that this method can acquire significant effect in the performance of reconstruction and recognition.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1. 3D Face Reconstruction
  2.2. 3D Face Recognition
 3. RIFF Algorithm
  3.1. Basis Function Definition
  3.2. Decomposition of Face Region
  3.4. Obtaining the Control Matrix
 4. Implementation
  4.1. Implementation Diagram
  4.2. Preprocessing
  4.3. Face Regionalization
  4.4. Face Reconstruction
  4.5. Face Recognition
 5. Experimental Results
  5.1. Reconstruction Performance
  5.2. Recognition Performance
 6. Conclusion and Future Work
 References

키워드

저자

• Jiang Zhi-chao [ Beijing Information Science and Technology University, the faculty of Computer, Beijing 100001 China ]
• Mu Yong-min [ Beijing Information Science and Technology University, the faculty of Computer, Beijing 100001 China ]
• Zhang Zhi-hua [ Beijing Information Science and Technology University, the faculty of Computer, Beijing 100001 China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605